71958

Автор(ы): 

Автор(ов): 

4

Параметры публикации

Тип публикации: 

Доклад

Название: 

Model for Analyzing Impact of Path Loss on eMBB Bit Rate Degradation Under Priority URLLC Transmission in 5G Network

ISBN/ISSN: 

978-3-031-23206-0

DOI: 

10.1007/978-3-031-23207-7_14

Наименование конференции: 

  • 25th International Conference on Distributed Computer and Communication Networks: Control, Computation, Communications (DCCN-2022)

Наименование источника: 

  • Lecture Note Computer Sciences (25th International Conference DCCN2022 Moscow)

Обозначение и номер тома: 

vol 13766

Город: 

  • London

Издательство: 

  • Springer

Год издания: 

2023

Страницы: 

176–189
Аннотация
One of the challenging tasks in 5G networks is to organize a joint URLLC (ultra-reliable and low-latency communication) and eMBB (enhanced mobile broadband) transmission in such a way that provides the priority to URLLC connections. The eMBB users suffer quality of service degradation, primarily bit rate degradation, as well as service interruption. In the paper, we provide a queuing model for analyzing this effect depending on several path loss models. The queuing system is of type resource queuing system, where the resource has three-dimensional structure – frequency bandwidth, radio frame length, and transmitted signal power. Due to different URLLC and eMBB bit rate requirements, we use weighted round robin (WRR) resource allocation scheme. The stationary probability distribution depends on the conditional probabilities of session acceptance. We provide the formulas for calculating eMBB metrics – average bit rate, interruption probability, and blocking probability. A numerical example illustrates the impact of two path loss models for macro- and microcells on eMBB metrics.

Библиографическая ссылка: 

Кочеткова И.А., Макеева Е.Д., Агеева А.С., Горшенин А.К. Model for Analyzing Impact of Path Loss on eMBB Bit Rate Degradation Under Priority URLLC Transmission in 5G Network / Lecture Note Computer Sciences (25th International Conference DCCN2022 Moscow). London: Springer, 2023. vol 13766. С. 176–189.